معرفی
Junyang Wang is a Research Associate in the Department of Mathematics at Imperial College London's Faculty of Natural Sciences. His research focuses on Bayesian methodology with applications in sustainability and public health, including Bayesian computation, probabilistic numerics, and variational inference. He collaborates with Dr. Sarah Filippi on scalable Bayesian mixture models for clustering risk factor data, and with NCD-RisC on public health applications.
Previously, he worked on Bayesian statistical methods for material flow analysis in civil engineering. He holds a PhD in Statistics from Newcastle University (focused on Bayesian probabilistic numerical methods for differential equations) and a Mathematics degree from the University of Cambridge.
His work bridges computational statistics with real-world challenges, emphasizing interdisciplinary collaboration across environmental science, epidemiology, and engineering systems. Current projects aim to advance scalable Bayesian techniques for high-dimensional data and complex systems analysis.
